Abstract: A multi-channel recorder/encoder for collecting, integrating, synchronizing and recording medical or surgical data received as independent live or real-time data streams from one or more hardware units. The medical or surgical data relating to a live or real-time medical procedure. Example hardware units include a control interface, cameras, sensors, audio devices, and patient monitoring hardware. Further example systems may include a cloud based platform incorporating the encoder.

Abstract: A multi-channel recorder/encoder for collecting, integrating, synchronizing and recording medical or surgical data received as independent live or real-time data streams from one or more hardware units. The medical or surgical data relating to a live or real-time medical procedure. Example hardware units include a control interface, cameras, sensors, audio devices, and patient monitoring hardware. Further example systems may include a cloud based platform incorporating the encoder.

Abstract: A completely edible pet treat is releasably attachable to another object, such as a camera or a mobile device having a camera. The pet treat includes a 100% edible fastening member, shaped and sized to be releasably attached to the object, and a 100% edible remaining member integral with the fastening member, sized to be visible to a pet, when the pet treat is attached to the object.

Abstract: A computer implemented system for automatically recording and generating predictive outputs relating to a medical procedure is described. The system is augmented with biometric sensory data from a biometric sensor coupled to a body of a healthcare practitioner. The biometric sensory data is processed to obtain one or more time-synchronized data objects providing a proxy to an estimated stress level associated with the healthcare practitioner, and the one or more time-synchronized data objects are utilized to identify abnormality-related durations of time encapsulated in the form of time-based metadata tags. The time-based metadata tags are utilized to automatically modify characteristics of the recording or generating of predictive outputs to temporarily consume more computational processing resources during the abnormality-related durations of time.

Abstract: A multi-channel recorder/encoder for collecting, integrating, synchronizing and recording medical or surgical data received as independent live or real-time data streams from a plurality of hardware units. The medical or surgical data relating to a live or real-time medical procedure. Example hardware units include a control interface, cameras, sensors, audio devices, and patient monitoring hardware. Further example systems may include a cloud based platform incorporating the encoder.

Abstract: The present teaching relates to estimating one or more parameters on a system including a plurality of nodes. In one example, the system comprises: one or more learner nodes, each of which is configured for generating information related to a group of words for estimating the one or more parameters associated with a machine learning model; and a plurality of server nodes, each of which is configured for obtaining a plurality of sub-vectors each of which is a portion of a vector that represents a word in the group of words, updating the sub-vectors based at least partially on the information to generate a plurality of updated sub-vectors, and estimating at least one of the one or more parameters associated with the machine learning model based on the plurality of updated sub-vectors.

Abstract: Embodiments described herein may provide devices, systems, methods, and/or computer readable medium for adverse event detection and severity estimation in surgical videos. The system can train multiple models for adverse detection and severity estimation. The system can load selected models for real-time adverse event detection and severity estimation.

Abstract: An autonomous vehicle and a diagnosis method for the autonomous vehicle are provided. The autonomous vehicle includes a memory that stores a driving record of the vehicle and a processor that establishes a diagnosis plan. The vehicle diagnosis is performed while operating the vehicle autonomously, when a stopping period of the vehicle is greater than or equal to a predetermined reference period, based on the driving record.

Abstract: A multi-channel recorder/encoder for collecting, integrating, synchronizing and recording medical or surgical data received as independent live or real-time data streams from a plurality of hardware units. The medical or surgical data relating to a live or real-time medical procedure. Example hardware units include a control interface, cameras, sensors, audio devices, and patient monitoring hardware. Further example systems may include a cloud based platform incorporating the encoder.

Abstract: The present teaching relates to estimating one or more parameters on a system including a plurality of nodes. In one example, the system comprises: one or more learner nodes, each of which is configured for generating information related to a group of words for estimating the one or more parameters associated with a machine learning model; and a plurality of server nodes, each of which is configured for obtaining a plurality of sub-vectors each of which is a portion of a vector that represents a word in the group of words, updating the sub-vectors based at least partially on the information to generate a plurality of updated sub-vectors, and estimating at least one of the one or more parameters associated with the machine learning model based on the plurality of updated sub-vectors.

Abstract: The present teaching relates to estimating one or more parameters on a system including a plurality of nodes. In one example, the system comprises: one or more learner nodes, each of which is configured for generating information related to a group of words for estimating the one or more parameters associated with a machine learning model; and a plurality of server nodes, each of which is configured for obtaining a plurality of sub-vectors each of which is a portion of a vector that represents a word in the group of words, updating the sub-vectors based at least partially on the information to generate a plurality of updated sub-vectors, and estimating at least one of the one or more parameters associated with the machine learning model based on the plurality of updated sub-vectors.

Abstract: A multi-channel recorder/encoder for collecting, integrating, synchronizing and recording medical or surgical data received as independent live or real-time data streams from a plurality of hardware units. The medical or surgical data relating to a live or real-time medical procedure. Example hardware units include a control interface, cameras, sensors, audio devices, and patient monitoring hardware. Further example systems may include a cloud based platform incorporating the encoder.

Abstract: A computer implemented system for automatically recording and generating predictive outputs relating to a medical procedure is described. The system is augmented with biometric sensory data from a biometric sensor coupled to a body of a healthcare practitioner. The biometric sensory data is processed to obtain one or more time-synchronized data objects providing a proxy to an estimated stress level associated with the healthcare practitioner, and the one or more time-synchronized data objects are utilized to identify abnormality-related durations of time encapsulated in the form of time-based metadata tags. The time-based metadata tags are utilized to automatically modify characteristics of the recording or generating of predictive outputs to temporarily consume more computational processing resources during the abnormality-related durations of time.

Abstract: The present teaching relates to estimating one or more parameters on a system including a plurality of nodes. In one example, the system comprises: one or more learner nodes, each of which is configured for generating information related to a group of words for estimating the one or more parameters associated with a machine learning model; and a plurality of server nodes, each of which is configured for obtaining a plurality of sub-vectors each of which is a portion of a vector that represents a word in the group of words, updating the sub-vectors based at least partially on the information to generate a plurality of updated sub-vectors, and estimating at least one of the one or more parameters associated with the machine learning model based on the plurality of updated sub-vectors.

Abstract: An autonomous vehicle and a diagnosis method for the autonomous vehicle are provided. The autonomous vehicle includes a memory that stores a driving record of the vehicle and a processor that establishes a diagnosis plan. The vehicle diagnosis is performed while operating the vehicle autonomously, when a stopping period of the vehicle is greater than or equal to a predetermined reference period, based on the driving record.

Abstract: The present teaching relates to estimating one or more parameters on a system including a plurality of nodes. In one example, the system comprises: one or more learner nodes, each of which is configured for generating information related to a group of words for estimating the one or more parameters associated with a machine learning model; and a plurality of server nodes, each of which is configured for obtaining a plurality of sub-vectors each of which is a portion of a vector that represents a word in the group of words, updating the sub-vectors based at least partially on the information to generate a plurality of updated sub-vectors, and estimating at least one of the one or more parameters associated with the machine learning model based on the plurality of updated sub-vectors.

Abstract: Embodiments described herein may provide devices, systems, methods, and/or computer readable medium for adverse event detection and severity estimation in surgical videos. The system can train multiple models for adverse detection and severity estimation. The system can load selected models for real-time adverse event detection and severity estimation.

Abstract: A multi-channel recorder/encoder for collecting, integrating, synchronizing and recording medical or surgical data received as independent live or real-time data streams from a plurality of hardware units. The medical or surgical data relating to a live or real-time medical procedure. Example hardware units include a control interface, cameras, sensors, audio devices, and patient monitoring hardware. Further example systems may include a cloud based platform incorporating the encoder.

Abstract: A new game and the methods thereof are disclosed. The game comprises utilizing new devices, rules, methods, well-defined terms, and a plurality of playing cards designed with special markings and performing alternative actions within a conditional loop to tactically and strategically form the cards on-hand as required melds/pair with bonus-earning patterns. The structure, format, rules, and playing methods of the present invention are designed to provide a great mental workout, and the purpose of the present invention is to engage people and create a friendly and gregarious environment that allows everyone to enjoy the company of others.

Abstract: There is provided p-type organic polymers of general formula I. The polymers may be useful as semi-conducting material. Thus, thin films and devices comprising such polymers are also provided.